SLEEP 2021 PRESENTATION — SleepIQ^® data to predict illness & COVID-19 symptom exacerbation

1. OBJECTIVE

This presentation illustrates a model by which symptoms for COVID-19 can be detected from the SleepIQ^® technology platform.

2. HIGH LEVEL STUDY SETUP

Using an Institutional Review Board (IRB) approved survey to opted-in users, COVID-19 test results were received. Data for 82 respondents who tested positive who reported the date of symptom onset were used. Data for 1,519 respondents who tested negative who reported testing dates were used. Sleep duration, sleep quality, restful sleep duration, time to fall asleep, respiration rate, heart rate, and motion level were obtained from ballistocardiography signals stored in the cloud.

3. RESULTS

With respect to their baseline, significant increases in sleep duration, average breathing rate, average heart rate and decrease in sleep quality were associated with symptom exacerbation in COVID-19 positive respondents. In COVID-19 negative respondents, no significant sleep or cardiorespiratory metrics were observed. Accuracy of the predictive model is similar to values reported for wearable sensors. Considering additional days to confirm prediction improved the accuracy.